Literature DB >> 18936489

Asymmetric disassembly and robustness in declining networks.

Serguei Saavedra1, Felix Reed-Tsochas, Brian Uzzi.   

Abstract

Mechanisms that enable declining networks to avert structural collapse and performance degradation are not well understood. This knowledge gap reflects a shortage of data on declining networks and an emphasis on models of network growth. Analyzing >700,000 transactions between firms in the New York garment industry over 19 years, we tracked this network's decline and measured how its topology and global performance evolved. We find that favoring asymmetric (disassortative) links is key to preserving the topology and functionality of the declining network. Based on our findings, we tested a model of network decline that combines an asymmetric disassembly process for contraction with a preferential attachment process for regrowth. Our simulation results indicate that the model can explain robustness under decline even if the total population of nodes contracts by more than an order of magnitude, in line with our observations for the empirical network. These findings suggest that disassembly mechanisms are not simply assembly mechanisms in reverse and that our model is relevant to understanding the process of decline and collapse in a broad range of biological, technological, and financial networks.

Mesh:

Year:  2008        PMID: 18936489      PMCID: PMC2575443          DOI: 10.1073/pnas.0804740105

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  19 in total

1.  Emergence of scaling in random networks

Authors: 
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

2.  Specificity and stability in topology of protein networks.

Authors:  Sergei Maslov; Kim Sneppen
Journal:  Science       Date:  2002-05-03       Impact factor: 47.728

3.  Clustering and preferential attachment in growing networks.

Authors:  M E Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2001-07-26

4.  Scale-free networks from varying vertex intrinsic fitness.

Authors:  G Caldarelli; A Capocci; P De Los Rios; M A Muñoz
Journal:  Phys Rev Lett       Date:  2002-12-03       Impact factor: 9.161

5.  Large-scale topological and dynamical properties of the Internet.

Authors:  Alexei Vázquez; Romualdo Pastor-Satorras; Alessandro Vespignani
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-06-28

6.  Topology of the world trade web.

Authors:  Ma Angeles Serrano; Marián Boguñá
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2003-07-11

7.  Asymmetric coevolutionary networks facilitate biodiversity maintenance.

Authors:  Jordi Bascompte; Pedro Jordano; Jens M Olesen
Journal:  Science       Date:  2006-04-21       Impact factor: 47.728

8.  Response of complex food webs to realistic extinction sequences.

Authors:  U Thara Srinivasan; Jennifer A Dunne; John Harte; Neo D Martinez
Journal:  Ecology       Date:  2007-03       Impact factor: 5.499

9.  Synaptic reorganization in scaled networks of controlled size.

Authors:  Nathan R Wilson; Michael T Ty; Donald E Ingber; Mriganka Sur; Guosong Liu
Journal:  J Neurosci       Date:  2007-12-12       Impact factor: 6.167

10.  The Matthew effect in science. The reward and communication systems of science are considered.

Authors:  R K Merton
Journal:  Science       Date:  1968-01-05       Impact factor: 47.728

View more
  13 in total

1.  What North America's skeleton crew of megafauna tells us about community disassembly.

Authors:  Matt Davis
Journal:  Proc Biol Sci       Date:  2017-01-11       Impact factor: 5.349

2.  Strong contributors to network persistence are the most vulnerable to extinction.

Authors:  Serguei Saavedra; Daniel B Stouffer; Brian Uzzi; Jordi Bascompte
Journal:  Nature       Date:  2011-09-14       Impact factor: 49.962

3.  Robustness elasticity in complex networks.

Authors:  Timothy C Matisziw; Tony H Grubesic; Junyu Guo
Journal:  PLoS One       Date:  2012-07-10       Impact factor: 3.240

4.  Automatic network fingerprinting through single-node motifs.

Authors:  Christoph Echtermeyer; Luciano da Fontoura Costa; Francisco A Rodrigues; Marcus Kaiser
Journal:  PLoS One       Date:  2011-01-31       Impact factor: 3.240

5.  The effect of selection bias in studies of fads and fashions.

Authors:  Jerker Denrell; Balázs Kovács
Journal:  PLoS One       Date:  2015-04-17       Impact factor: 3.240

6.  Do scientists trace hot topics?

Authors:  Tian Wei; Menghui Li; Chensheng Wu; Xiao-Yong Yan; Ying Fan; Zengru Di; Jinshan Wu
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

7.  Network strategies to understand the aging process and help age-related drug design.

Authors:  Gábor I Simkó; Dávid Gyurkó; Dániel V Veres; Tibor Nánási; Peter Csermely
Journal:  Genome Med       Date:  2009-09-28       Impact factor: 11.117

8.  Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks.

Authors:  Boris Podobnik; Tomislav Lipic; Davor Horvatic; Antonio Majdandzic; Steven R Bishop; H Eugene Stanley
Journal:  Sci Rep       Date:  2015-09-21       Impact factor: 4.379

9.  Uncovering the role of elementary processes in network evolution.

Authors:  Gourab Ghoshal; Liping Chi; Albert-László Barabási
Journal:  Sci Rep       Date:  2013-10-10       Impact factor: 4.379

10.  Cascading collapse of online social networks.

Authors:  János Török; János Kertész
Journal:  Sci Rep       Date:  2017-12-01       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.